CData Python Connector for Google Cloud Storage

Build 24.0.9060

From Pandas

When combined with the connector, Pandas can be used to generate data frames that contain your Google Cloud Storage data. Once created, a data frame can be passed to various other Python packages.

Connecting

Pandas relies on an SQLAlchemy engine to execute queries. Before you can use Pandas you must import it:
import pandas as pd
from sqlalchemy import create_engine
engine = create_engine("googlecloudstorage:///?InitiateOAuth=GETANDREFRESH;ProjectId='project1';")

Querying Data

In Pandas, SELECT queries are provided in a call to the read_sql() method, alongside a relevant connection object. Pandas executes the query on that connection, and returns the results in the form of a data frame, which can be used for a variety of purposes.
df = pd.read_sql("""
	SELECT
	   Name,
	   OwnerId,
     $exNumericCol;
	FROM Buckets;""", engine)
print(df)

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Build 24.0.9060